Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Sep 2021
Research article |
| 22 Sep 2021
| 22 Sep 2021
A comparison of tools and techniques for stabilising unmanned aerial system (UAS) imagery for surface flow observations
Robert Ljubičić
CORRESPONDING AUTHOR
Department of Hydraulic and Environmental Engineering, Faculty of
Civil Engineering, University of Belgrade, Belgrade 11120, Serbia
Dariia Strelnikova
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Matthew T. Perks
School of Geography, Politics and Sociology, Newcastle University,
Newcastle upon Tyne NE1 7RU, United Kingdom
Anette Eltner
Institute of Photogrammetry and Remote Sensing, Technische
Universität Dresden, 01069 Dresden, Germany
Salvador Peña-Haro
Photrack AG, Ankerstrasse 16a, 8004 Zurich, Switzerland
Alonso Pizarro
Escuela de Ingeniería en Obras Civiles, Universidad Diego
Portales, 8370109 Santiago, Chile
Silvano Fortunato Dal Sasso
Department of European and Mediterranean Cultures: Architecture,
Environment and Cultural Heritage (DICEM), University of Basilicata, 75100
Matera, Italy
Ulf Scherling
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Pietro Vuono
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
Salvatore Manfreda
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
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Oliver Grothum, Lea Epple, Anne Bienert, Xabier Blanch, and Anette Eltner
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Felix Rocco Matzke, Tushar Jayesh Barot, Shreeja Sridharan, Nikolaus Ammann, Christoph Kessler, Hans-Gerd Maas, Frank H. P. Fitzek, and Anette Eltner
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Domenico Miglino, Seifeddine Jomaa, Michael Rode, Khim Cathleen Saddi, Francesco Isgrò, and Salvatore Manfreda
Hydrol. Earth Syst. Sci., 29, 4133–4151, https://doi.org/10.5194/hess-29-4133-2025, https://doi.org/10.5194/hess-29-4133-2025, 2025
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Matthew T. Perks, Borbála Hortobágyi, Nick Everard, Susan Manson, Juliet Rowland, Andrew Large, and Andrew J. Russell
Hydrol. Earth Syst. Sci., 29, 3727–3743, https://doi.org/10.5194/hess-29-3727-2025, https://doi.org/10.5194/hess-29-3727-2025, 2025
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Hanne Hendrickx, Melanie Elias, Xabier Blanch, Reynald Delaloye, and Anette Eltner
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Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
Hydrol. Earth Syst. Sci., 29, 465–483, https://doi.org/10.5194/hess-29-465-2025, https://doi.org/10.5194/hess-29-465-2025, 2025
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Qianqian Han, Yijian Zeng, Lijie Zhang, Calimanut-Ionut Cira, Egor Prikaziuk, Ting Duan, Chao Wang, Brigitta Szabó, Salvatore Manfreda, Ruodan Zhuang, and Bob Su
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Using machine learning, we estimated global surface soil moisture (SSM) to aid in understanding water, energy, and carbon exchange. Ensemble models outperformed individual algorithms in predicting SSM under different climates. The best-performing ensemble included K-neighbours Regressor, Random Forest Regressor, and Extreme Gradient Boosting. This is important for hydrological and climatological applications such as water cycle monitoring, irrigation management, and crop yield prediction.
R. Blaskow and A. Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 45–50, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-45-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-45-2023, 2023
Gernot Paulus, Dariia Strelnikova, Thomas Lutz, Karl-Heinrich Anders, Klaus Gäbler, Gerhard Lippitsch, Daniela Meier, and Stefan Eisenbach
AGILE GIScience Ser., 3, 51, https://doi.org/10.5194/agile-giss-3-51-2022, https://doi.org/10.5194/agile-giss-3-51-2022, 2022
Enrico Tubaldi, Christopher J. White, Edoardo Patelli, Stergios Aristoteles Mitoulis, Gustavo de Almeida, Jim Brown, Michael Cranston, Martin Hardman, Eftychia Koursari, Rob Lamb, Hazel McDonald, Richard Mathews, Richard Newell, Alonso Pizarro, Marta Roca, and Daniele Zonta
Nat. Hazards Earth Syst. Sci., 22, 795–812, https://doi.org/10.5194/nhess-22-795-2022, https://doi.org/10.5194/nhess-22-795-2022, 2022
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Bridges are critical infrastructure components of transport networks. A large number of these critical assets cross or are adjacent to waterways and are therefore exposed to the potentially devastating impact of floods. This paper discusses a series of issues and areas where improvements in research and practice are required in the context of risk assessment and management of bridges exposed to flood hazard, with the ultimate goal of guiding future efforts in improving bridge flood resilience.
Lea Epple, Andreas Kaiser, Marcus Schindewolf, and Anette Eltner
SOIL Discuss., https://doi.org/10.5194/soil-2021-85, https://doi.org/10.5194/soil-2021-85, 2021
Revised manuscript not accepted
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Intensified extreme weather events due to climate change can result in changes of soil erosion. These unclear developments make an improvement of soil erosion modelling all the more important. Assuming that soil erosion models cannot keep up with the current data, this work gives an overview of 44 models, their strengths and weaknesses and discusses their potential for further development with respect to new and improved soil and soil erosion assessment techniques.
Salvatore Manfreda, Domenico Miglino, and Cinzia Albertini
Hydrol. Earth Syst. Sci., 25, 4231–4242, https://doi.org/10.5194/hess-25-4231-2021, https://doi.org/10.5194/hess-25-4231-2021, 2021
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In this work, we introduce a new theoretically derived probability distribution of the outflows of in-line detention dams. The method may be used to evaluate the impact of detention dams on flood occurrences and attenuation of floods. This may help and support risk management planning and design.
A. Eltner, D. Mader, N. Szopos, B. Nagy, J. Grundmann, and L. Bertalan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 717–722, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-717-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-717-2021, 2021
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Short summary
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed widespread use of image velocimetry techniques in place of more traditional, usually slower, methods during hydrometric campaigns. In order to minimize the velocity estimation errors, one must stabilise the acquired videos. In this research, we compare the performance of different UAS video stabilisation tools and provide guidelines for their use in videos with different flight and ground conditions.
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed...
